Prometheus exporter for Cisco Unified Computing System (UCS) Manager

Overview

prometheus-ucs-exporter

Overview

Use metrics from the UCS API to export relevant metrics to Prometheus

This repository is a fork of Drew Stinnett's original exporter at oit-ssi-systems/prometheus-ucs-exporter.

Modifications made include:

  • Added production server (FastAPI)
  • Added additional metrics
  • Added Grafana dashboard
  • Minor fixes and refactorings

Install the Grafana dashboard by importing the JSON file grafana/dashboard.json.

Cisco UCSM Grafana dashboard

Installation

Build and run with Docker:

docker build -t prometheus-ucs-exporter .

docker run -p 3001:3001 -e PORT=3001 \
-e PROM_UCS_USERNAME='ucs-mydomain\username' \
-e PROM_UCS_PASSWORD='passw0rd' \
prometheus-ucs-exporter

Fetch metrics:

curl http://localhost:3001/metrics?domain=my-domain.example.com

Note: Metrics are fetched in a background worker after an initial scrape, since UCSM can be slow to respond. Continue polling the /metrics endpoint until metrics are returned.

Usage

docker pull ghcr.io/marshallwace/prometheus-ucs-exporter:0.0.2

SPDX update

pip install --user pipx

pipx run reuse addheader --copyright "2022 Marshall Wace <[email protected]>" --license "GPL-3.0-only" *.py 
You might also like...
Numenta Platform for Intelligent Computing is an implementation of Hierarchical Temporal Memory (HTM), a theory of intelligence based strictly on the neuroscience of the neocortex.

NuPIC Numenta Platform for Intelligent Computing The Numenta Platform for Intelligent Computing (NuPIC) is a machine intelligence platform that implem

xitorch: differentiable scientific computing library

xitorch is a PyTorch-based library of differentiable functions and functionals that can be widely used in scientific computing applications as well as deep learning.

A static analysis library for computing graph representations of Python programs suitable for use with graph neural networks.

python_graphs This package is for computing graph representations of Python programs for machine learning applications. It includes the following modu

Blender scripts for computing geodesic distance
Blender scripts for computing geodesic distance

GeoDoodle Geodesic distance computation for Blender meshes Table of Contents Overivew Usage Implementation Overview This addon provides an operator fo

Lyapunov-guided Deep Reinforcement Learning for Stable Online Computation Offloading in Mobile-Edge Computing Networks

PyTorch code to reproduce LyDROO algorithm [1], which is an online computation offloading algorithm to maximize the network data processing capability subject to the long-term data queue stability and average power constraints. It applies Lyapunov optimization to decouple the multi-stage stochastic MINLP into deterministic per-frame MINLP subproblems and solves each subproblem via DROO algorithm. It includes:

Library for implementing reservoir computing models (echo state networks) for multivariate time series classification and clustering.
Library for implementing reservoir computing models (echo state networks) for multivariate time series classification and clustering.

Framework overview This library allows to quickly implement different architectures based on Reservoir Computing (the family of approaches popularized

Material related to the Principles of Cloud Computing course.

CloudComputingCourse Material related to the Principles of Cloud Computing course. This repository comprises material that I use to teach my Principle

Code for the paper "Next Generation Reservoir Computing"

Next Generation Reservoir Computing This is the code for the results and figures in our paper "Next Generation Reservoir Computing". They are written

Differentiable scientific computing library

xitorch: differentiable scientific computing library xitorch is a PyTorch-based library of differentiable functions and functionals that can be widely

Comments
  • How to support polling multiple UCS Domains

    How to support polling multiple UCS Domains

    Is it possible to support polling of multiple UCS domains using a single prometheus instance or is it better to dedicate a prmetheus container to each UCS domain?

    opened by dwebr 1
  • UCS System returns

    UCS System returns "not-applicable" for kernel_mem_total and kernel_mem_free stats

    Issue: UCS running version 4.2(1m)B returns "not-applicable" for kernel_mem_total and kernel_mem_free stats which results in prometheus throwing errors during polling.

    Work around: comment out the following statements in the swsystem.py file.

    kernel_mem_total.labels(self.domain, switch).set(int(item.kernel_mem_total))
    kernel_mem_free.labels(self.domain, switch).set(int(item.kernel_mem_free))
    

    Example Output

    /repos/prometheus-ucs-exporter/scripts$ ./explore.py query-classid swSystemStats
    
    Managed Object                  :       SwSystemStats
    --------------
    class_id                        :SwSystemStats
    child_action                    :None
    correctable_parity_error        :not-applicable
    correctable_parity_error_avg    :not-applicable
    correctable_parity_error_max    :not-applicable
    correctable_parity_error_min    :not-applicable
    dn                              :sys/switch-B/sysstats
    intervals                       :58982460
    kernel_mem_free                 :not-applicable
    kernel_mem_free_avg             :not-applicable
    kernel_mem_free_max             :not-applicable
    kernel_mem_free_min             :not-applicable
    kernel_mem_total                :not-applicable
    kernel_mem_total_avg            :not-applicable
    kernel_mem_total_max            :not-applicable
    kernel_mem_total_min            :not-applicable
    load                            :2.360000
    load_avg                        :2.413333
    load_max                        :2.620000
    load_min                        :2.130000
    mem_available                   :52264
    mem_available_avg               :52278
    mem_available_max               :52302
    mem_available_min               :52264
    mem_cached                      :11591
    mem_cached_avg                  :11576
    mem_cached_max                  :11591
    mem_cached_min                  :11563
    rn                              :sysstats
    sacl                            :None
    status                          :None
    suspect                         :no
    thresholded                     :
    time_collected                  :2022-09-24T10:13:48.368
    update                          :131081
    
    
    
    Managed Object                  :       SwSystemStats
    --------------
    class_id                        :SwSystemStats
    child_action                    :None
    correctable_parity_error        :not-applicable
    correctable_parity_error_avg    :not-applicable
    correctable_parity_error_max    :not-applicable
    correctable_parity_error_min    :not-applicable
    dn                              :sys/switch-A/sysstats
    intervals                       :58982460
    kernel_mem_free                 :not-applicable
    kernel_mem_free_avg             :not-applicable
    kernel_mem_free_max             :not-applicable
    kernel_mem_free_min             :not-applicable
    kernel_mem_total                :not-applicable
    kernel_mem_total_avg            :not-applicable
    kernel_mem_total_max            :not-applicable
    kernel_mem_total_min            :not-applicable
    load                            :3.820000
    load_avg                        :2.701667
    load_max                        :3.820000
    load_min                        :2.090000
    mem_available                   :52062
    mem_available_avg               :52050
    mem_available_max               :52062
    mem_available_min               :52036
    mem_cached                      :11060
    mem_cached_avg                  :11068
    mem_cached_max                  :11083
    mem_cached_min                  :11060
    rn                              :sysstats
    sacl                            :None
    status                          :None
    suspect                         :no
    thresholded                     :
    time_collected                  :2022-09-24T10:14:32.366
    update                          :131078
    
    bug 
    opened by dwebr 0
Releases(v0.0.2)
Owner
Marshall Wace
Marshall Wace
Convenient tool for speeding up the intern/officer review process.

icpc-app-screen Convenient tool for speeding up the intern/officer applicant review process. Eliminates the pain from reading application responses of

1 Oct 30, 2021
Motion Planner Augmented Reinforcement Learning for Robot Manipulation in Obstructed Environments (CoRL 2020)

Motion Planner Augmented Reinforcement Learning for Robot Manipulation in Obstructed Environments [Project website] [Paper] This project is a PyTorch

Cognitive Learning for Vision and Robotics (CLVR) lab @ USC 49 Nov 28, 2022
Yolov3 pytorch implementation

YOLOV3 Pytorch实现 在bubbliiing大佬代码的基础上进行了修改,添加了部分注释。 预训练模型 预训练模型来源于bubbliiing。 链接:https://pan.baidu.com/s/1ncREw6Na9ycZptdxiVMApw 提取码:appk 训练自己的数据集 按照VO

4 Aug 27, 2022
The Python3 import playground

The Python3 import playground I have been confused about python modules and packages, this text tries to clear the topic up a bit. Sources: https://ch

Michael Moser 5 Feb 22, 2022
YouRefIt: Embodied Reference Understanding with Language and Gesture

YouRefIt: Embodied Reference Understanding with Language and Gesture YouRefIt: Embodied Reference Understanding with Language and Gesture by Yixin Che

16 Jul 11, 2022
A novel framework to automatically learn high-quality scanning of non-planar, complex anisotropic appearance.

appearance-scanner About This repository is an implementation of the neural network proposed in Free-form Scanning of Non-planar Appearance with Neura

Xiaohe Ma 14 Oct 18, 2022
STEAL - Learning Semantic Boundaries from Noisy Annotations (CVPR 2019)

STEAL This is the official inference code for: Devil Is in the Edges: Learning Semantic Boundaries from Noisy Annotations David Acuna, Amlan Kar, Sanj

469 Dec 26, 2022
A simple command line tool for text to image generation, using OpenAI's CLIP and a BigGAN.

Ryan Murdock has done it again, combining OpenAI's CLIP and the generator from a BigGAN! This repository wraps up his work so it is easily accessible to anyone who owns a GPU.

Phil Wang 2.3k Jan 09, 2023
Aiming at the common training datsets split, spectrum preprocessing, wavelength select and calibration models algorithm involved in the spectral analysis process

Aiming at the common training datsets split, spectrum preprocessing, wavelength select and calibration models algorithm involved in the spectral analysis process, a complete algorithm library is esta

Fu Pengyou 50 Jan 07, 2023
Neural networks applied in recognizing guitar chords using python, AutoML.NET with C# and .NET Core

Chord Recognition Demo application The demo application is written in C# with .NETCore. As of July 9, 2020, the only version available is for windows

Andres Mauricio Rondon Patiño 24 Oct 22, 2022
ruptures: change point detection in Python

Welcome to ruptures ruptures is a Python library for off-line change point detection. This package provides methods for the analysis and segmentation

Charles T. 1.1k Jan 03, 2023
PEPit is a package enabling computer-assisted worst-case analyses of first-order optimization methods.

PEPit: Performance Estimation in Python This open source Python library provides a generic way to use PEP framework in Python. Performance estimation

Baptiste 53 Nov 16, 2022
Code repository for our paper regarding the L3D dataset.

The Large Labelled Logo Dataset (L3D): A Multipurpose and Hand-Labelled Continuously Growing Dataset Website: https://lhf-labs.github.io/tm-dataset Da

LHF Labs 9 Dec 14, 2022
Satellite labelling tool for manual labelling of storm top features such as overshooting tops, above-anvil plumes, cold U/Vs, rings etc.

Satellite labelling tool About this app A tool for manual labelling of storm top features such as overshooting tops, above-anvil plumes, cold U/Vs, ri

Czech Hydrometeorological Institute - Satellite Department 10 Sep 14, 2022
Official implementation of "UCTransNet: Rethinking the Skip Connections in U-Net from a Channel-wise Perspective with Transformer"

[AAAI2022] UCTransNet This repo is the official implementation of "UCTransNet: Rethinking the Skip Connections in U-Net from a Channel-wise Perspectiv

Haonan Wang 199 Jan 03, 2023
Tensorboard for pytorch (and chainer, mxnet, numpy, ...)

tensorboardX Write TensorBoard events with simple function call. The current release (v2.3) is tested on anaconda3, with PyTorch 1.8.1 / torchvision 0

Tzu-Wei Huang 7.5k Dec 28, 2022
Minimalistic PyTorch training loop

Backbone for PyTorch training loop Will try to keep it minimalistic. pip install back from back import Bone Features Progress bar Checkpoints saving/l

Kashin 4 Jan 16, 2020
A benchmark dataset for mesh multi-label-classification based on cube engravings introduced in MeshCNN

Double Cube Engravings This script creates a dataset for multi-label mesh clasification, with an intentionally difficult setup for point cloud classif

Yotam Erel 1 Nov 30, 2021
ICLR 2021 i-Mix: A Domain-Agnostic Strategy for Contrastive Representation Learning

Introduction PyTorch code for the ICLR 2021 paper [i-Mix: A Domain-Agnostic Strategy for Contrastive Representation Learning]. @inproceedings{lee2021i

Kibok Lee 68 Nov 27, 2022
[ICCV 2021] Code release for "Sub-bit Neural Networks: Learning to Compress and Accelerate Binary Neural Networks"

Sub-bit Neural Networks: Learning to Compress and Accelerate Binary Neural Networks By Yikai Wang, Yi Yang, Fuchun Sun, Anbang Yao. This is the pytorc

Yikai Wang 26 Nov 20, 2022